Senior Analytics Engineer

About the role

Polymarket is seeking a Senior Analytics Engineer to own the critical modeling layer that bridges raw data and high-impact business decisions. In this role, you will define the foundational logic and calculations that underpin key business metrics, ensuring consistency and trust across the organization. You will design and maintain dbt models that transform diverse inputs, including platform events and on-chain activity, into reliable datasets ready for analysis. The ideal candidate will partner closely with data engineers and data scientists to optimize the data warehouse for performance, cost, and clarity. You will be responsible for translating ambiguous questions from stakeholders into durable analytical solutions rather than temporary fixes. A strong focus on documentation and self-service will empower growth, finance, and market operations teams to explore data independently. You will also implement monitoring and testing practices to catch data quality issues early and protect decision-making. This position is central to enabling the rapid launch of new products and market types in a fast-evolving environment.

Key facts

What you'll do

• Design and build dbt models that convert raw platform, on-chain and off-chain trading activity, and third-party data into trusted, well-documented datasets.
• Own the definitions of core metrics such as volume, traders, retention, acquisition cost, and revenue to ensure consistent interpretation across all dashboards and conversations.
• Collaborate with data engineers on warehouse architecture, including materialized views, incremental models, query performance, and cost optimization.
• Build and maintain reporting in homegrown Vercel dashboards and Hex, enabling growth, marketing, finance, and markets teams to access self-serve insights.
• Work directly with stakeholders to convert open-ended questions into durable models that deliver answers without requiring repeated data intervention.
• Implement tests and monitoring at the model layer so data quality issues are identified before they appear in board-level presentations.
• Model new products and market types as they launch, ensuring the semantic layer keeps pace with a business that evolves on a weekly basis.
• Produce end-to-end documentation that is clear and thorough enough for any engineer or analyst on the team to context-switch into your models with minimal friction.
• Partner with cross-functional teams to understand requirements and translate them into analytical structures that support long-term decision-making.
• Optimize data pipelines to handle high-volume trading datasets while maintaining query speed and reliability under load.
• Serve as the primary contact for questions related to metric logic, data definitions, and calculation methodologies across the organization.
• Drive adoption of best practices in version control, code review, and modular modeling to improve long-term maintainability.
• Identify opportunities to automate routine analytical tasks, reducing manual effort and increasing scalability.
• Contribute to the broader data strategy by providing insights on tooling, architecture, and process improvements.

Requirements

• 7+ years of experience in analytics engineering, data analytics, or a similar role, with production experience owning a modeling layer.
• Expert SQL skills, with the ability to read, write, and optimize complex queries against high-volume datasets.
• Hands-on experience with dbt or equivalent tools, Airflow or other orchestration solutions, and a modern cloud warehouse such as Databricks, Snowflake, BigQuery, or ClickHouse.
• Strong instincts for dimensional modeling and metric design, including the judgment to know when to denormalize for performance or clarity.
• Fluency with BI tooling such as Hex, Looker, or similar, and a bias toward building for self-serve over fulfilling one-off requests.
• Enough software engineering fundamentals to work comfortably in version control, review others' code, and keep a project maintainable over time.
• Genuine interest in understanding the business drivers behind the metrics, not just running queries and models.
• Comfortable operating in a fast-moving environment where business logic changes frequently and you need to adapt quickly without losing quality.
• (Plus) Familiarity with on-chain data or blockchain analytics.
• (Plus) Experience in fintech, crypto, prediction markets, or other data-intensive financial products.

Nice to have

Only items explicitly noted as preferred in the source description are included here, and they appear as the two (Plus) lines in the requirements section above. No additional preferences are introduced.

Practical notes

The position is full-time based in New York. The compensation details are not specified in the source material and are therefore omitted. No information regarding hours, travel requirements, visa sponsorship, or application deadlines is provided in the source, so those details are not included here.